Public Opinion and Sentiment Before and at the Beginning of COVID-19 Vaccinations in Japan: Twitter Analysis

  1. Qian Niu
  2. Junyu Liu
  3. Masaya Kato
  4. Yuki Shinohara
  5. Natsuki Matsumura
  6. Tomoki Aoyama
  7. Momoko Nagai-Tanima

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Abstract

COVID-19 vaccines are considered one of the most effective ways for containing the COVID-19 pandemic, but Japan lagged behind other countries in vaccination in the early stages. A deeper understanding of the slow progress of vaccination in Japan can be instructive for COVID-19 booster vaccination and vaccinations during future pandemics.

Objective

This retrospective study aims to analyze the slow progress of early-stage vaccination in Japan by exploring opinions and sentiment toward the COVID-19 vaccine in Japanese tweets before and at the beginning of vaccination.

Methods

We collected 144,101 Japanese tweets containing COVID-19 vaccine-related keywords between August 1, 2020, and June 30, 2021. We visualized the trend of the tweets and sentiments and identified the critical events that may have triggered the surges. Correlations between sentiments and the daily infection, death, and vaccination cases were calculated. The latent dirichlet allocation model was applied to identify topics of negative tweets from the beginning of vaccination. We also conducted an analysis of vaccine brands (Pfizer, Moderna, AstraZeneca) approved in Japan.

Results

The daily number of tweets continued with accelerating growth after the start of large-scale vaccinations in Japan. The sentiments of around 85% of the tweets were neutral, and negative sentiment overwhelmed the positive sentiment in the other tweets. We identified 6 public-concerned topics related to the negative sentiment at the beginning of the vaccination process. Among the vaccines from the 3 manufacturers, the attitude toward Moderna was the most positive, and the attitude toward AstraZeneca was the most negative.

Conclusions

Negative sentiment toward vaccines dominated positive sentiment in Japan, and the concerns about side effects might have outweighed fears of infection at the beginning of the vaccination process. Topic modeling on negative tweets indicated that the government and policy makers should take prompt actions in building a safe and convenient vaccine reservation and rollout system, which requires both flexibility of the medical care system and the acceleration of digitalization in Japan. The public showed different attitudes toward vaccine brands. Policy makers should provide more evidence about the effectiveness and safety of vaccines and rebut fake news to build vaccine confidence.

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  1. Version published to 10.2196/32335
  2. Version published to 10.1101/2021.07.19.21260735v2 on medRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.07.19.21260735: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The Python package scikit-learn was used to convert the segmented sentences into unigram and bigram tokens and to calculate the counts of tokens.
    Python
    suggested: (IPython, RRID:SCR_001658)
    scikit-learn
    suggested: (scikit-learn, RRID:SCR_002577)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations: Although we attempted to analyze Japanese posts on Twitter to gauge public opinion and sentiment throughout Japan, our data may not be representative of the country’s population at large, especially the elderly. According to statista[42], in 2021, about 17% of the Twitter population worldwide is aged 50 or above, leaving 83% in the 49 or younger category. Goldstein et al. [43]showed that the cumulative rate of COVID-19 infection in the community is high among people younger than 35 years old, while transmission in middle or high schools is robust. The opinions of adults over 40 need to be further investigated by modifying the study design, but there is an urgent need to explore the opinions and acceptance of vaccination in younger populations. Moreover, according to Twitter’s user privacy protection principles, our study did not further examine the demographic characteristics of users, such as age, gender, and geographic location. Since large-scale vaccination began in Japan on May 24, 2021, our nearly year-long data analysis includes only one month after that time; thus, we will continue to monitor and conduct long-term trend analysis.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  4. Version published to 10.2196/preprints.32335
  5. Version published to 10.1101/2021.07.19.21260735v1 on medRxiv